Weljie Lab

Research

Primary research directions include:

1. Circadian Metabolomics.
   Recent studies in our lab and others demonstrate that metabolite outputs of classical biochemistry are highly influenced in a circadian fashion. For example, bioenergetic processes such as glycolysis, oxidative phosphorylation, redox pathways as well as biosynthetic processes such as ammonia metabolism and lipid metabolism all demonstrate strong circadian fluctuations. Lipids are of great interest due to their various functional and structural roles in cells and also demonstrate circadian cycling. This has dramatic implications both in terms of sleep (eg. Shiftwork leading to elevated levels of cancer, diabetes obsesity etc), as well as pharmacology and therapeutic windows for drug delivery and treatment.  We are also interested in the interaction of environmental factors in both circadian function and metabolic outputs, for example we are investigating tissue level changes of lipids and gene expression as function of fasting and light-dark cycle.
   
   In the long-term, we aim to develop molecular scale models of metabolic flux through circadian pathways building on expertise in quantitative nuclear magnetic resonance (NMR) spectroscopy metabolomics and mass spectrometry (MS). This entails organizing experimentation and data analysis in a highly multidisciplinary and dynamic environment with the demands of analytical chemistry, statistics, biology and medicine. 
    
2. Diagnostic metabolite profiling for biomarker discovery.
   High-throughput metabolite profiling has great potential in the development of clinical diagnostic and prognostic tests. We are involved in a number of highly-collaborative animal and clinical studies aimed at using metabolomics methods as an additional tool in the clinic. Some of our specific projects include investigating the metabolic signatures of sleep deprivation, insomnia, Thalassemia, Alzheimer’s disease risk, and select medical drugs.
   
   While great progress has been made in the field over the past several years, clear need for additional methods are still present. A particular area of interest is development of proper biofluid sample analysis protocols and statistical good practices in metabolomics analyses using mass spectrometry for polar and lipid analysis. We are also actively studying pre-analytical variation in metabolomics samples with the goal of developing good practices for the design of clinical metabolomics protocols. 
    
3. Analytical Tool Development
   Our lab specializes in the application of analytical technologies such as NMR and LC-MS to profile small molecules in biological samples. This is often referred to as metabolite profiling, and when combined with advanced multivariate statistical tools, given the moniker of ‘metabolomics’ or ‘metabonomics’.
   
   This research area can be viewed as the metabolite analogue to genomic, proteomics and transcriptomics technologies. High-throughput metabolite profiling has great potential in the development of clinical diagnostic and prognostic tests (Medina et al, Current Medicinal Chemistry, 2014; Madsen et al, Analytica chimica acta, 2009). Excellent summaries of metabolomics can be found on the websites of Dr. Mark Viant, Dr. Jules Griffin, and Dr. Oliver Fiehn. A set of tutorials can be fond on the Metabolomics Society website.

The Weljie Lab is equipped with:

• A high-resolution 700 MHz NMR spectrometer equipped with 3 and 5 mm TXI probes and a SampleJet autosampler with dedicated cooling enabling robust and stable high throughput acquisition of NMR metabolomics data.
• A dedicated LC-SPE system coupled to an Gilsen liquid handler for purification of low-concentration compounds for NMR analysis.
• A Waters Xevo TQD triple-quadrupole mass spectrometer (QqQ) with Acquity ultraperformance liquid chromatography (UPLC).
• A Waters Xevo G2-S quadrupole time-of-flight mass spectrometer (QTOF) mass spectrometer equipped for both one-dimensional and two-dimensional Acquity UPLC.

These analytical platforms enable our state-of-the-art metabolite profiling approach.